Two-dimensional (2D) segmented cardiac cine Magnetic Resonance Imaging (MRI) is a time-resolved imaging technology that is routinely used for non-invasive assessment of the cardiac function. This technology requires breath-holds and a regular heartbeat from the individual being imaged. In situations where this is not possible, 2D unsegmented real-time Balanced Steady-State Free Precession (bSSFP) cine MRI, accelerated by parallel imaging and partial Fourier techniques, is often used with reduced quality. bSSFP requires short inter-pulse distance repetition time (TR) for robustness against BO field inhomogeneities and flow. In Cartesian bSSFP, the TR is reduced by partial Fourier acquisition in the readout direction (i.e., the early part of the echo is omitted and the readout is thus shortened). Reconstruction can use zero-filling or data generating algorithms like projection onto convex sets (POCS). The reduction in TR can be either used to increase the frame rate, or to increase the number of views per frame.
Recently, the idea of exploiting the compressibility of MR images in a transform domain has resulted in the development of compressed-sensing (CS) based MRI reconstruction techniques which can accelerate acquisition times in cardiac cine by enabling image reconstruction from highly undersampled k-space data. Some conventional imaging systems combine CS-type reconstruction techniques with radial sampling strategies to further reduce the overall time required to acquire and process images. These systems typically utilize views which are placed symmetrically around the k-space center to form full echoes for acquisition. However, the symmetric placement of views introduces a redundancy because it ignores the complex conjugate symmetry that exists between signals from the outer parts of the k-space connected by point symmetry. Accordingly, it is desired to provide techniques which exploit the complex conjugate symmetry that exists in k-space to further accelerate acquisition time.